Summary of the paper
| Title | Adapting VerbNet to French using Existing Resources |
|---|---|
| Authors | Quentin Pradet, Laurence Danlos and Gaël De Chalendar |
| Abstract | VerbNet is an English lexical resource for verbs that has proven useful for English NLP due to its high coverage and coherent classification. Such a resource doesn’t exist for other languages, despite some (mostly automatic and unsupervised) attempts. We show how to semi-automatically adapt VerbNet using existing resources designed for diļ¬erent purposes. This study focuses on French and uses two French resources: a semantic lexicon (Les Verbes Français) and a syntactic lexicon (Lexique-Grammaire). |
| Topics | Semantics, Grammar and Syntax |
Full paper  |
Adapting VerbNet to French using Existing Resources |
| Bibtex | @InProceedings{PRADET14.203, author = {Quentin Pradet and Laurence Danlos and Gaël De Chalendar}, title = {Adapting VerbNet to French using Existing Resources}, booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)}, year = {2014}, month = {may}, date = {26-31}, address = {Reykjavik, Iceland}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-8-4}, language = {english} } |